Sea-State-Aware Adaptive Filtering of Tidal Current Measurements under Wave- Induced Disturbances

Sea-State-Aware Adaptive Filtering of Tidal Current Measurements under Wave- Induced Disturbances | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sea-State-Aware Adaptive Filtering of Tidal Current Measurements under Wave- Induced Disturbances Ali Fituri, Abdelouahed Gherbi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9101238/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Reliable tidal current measurements are vital for monitoring and assessing the performance of tidal turbine systems and other marine energy applications. In practice, these measurements are often affected by stochastic disturbances and wave-induced fluctuations that vary with sea-state conditions. Standard adaptive filtering techniques, such as LMS and RLS, are commonly used to clean these signals, but their performance can decline when disturbances change dynamically. In this study, we introduce a sea-state-aware adaptive filtering framework that incorporates environmental wave information into the filter adaptation process. By considering sea-state variations, the filters can adjust dynamically to changing noise conditions, improving the recovery and reliability of tidal signals. The framework is tested on tidal current datasets under stochastic and wave-induced disturbances. Results show improved signal fidelity, reduced estimation errors, and more stable operation compared to conventional LMS and RLS filters. This approach offers a practical solution for reliable tidal turbine monitoring and can be applied to other coastal and offshore measurement systems influenced by wave-induced noise. Wave-aware adaptive filtering Least Mean Squares LMS Recursive Least Squares RLS Turbine operational conditions monitoring Environmental noise modeling non-stationary signal estimation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 18 May, 2026 Reviewers agreed at journal 27 Apr, 2026 Reviewers invited by journal 27 Apr, 2026 Editor assigned by journal 14 Mar, 2026 Submission checks completed at journal 14 Mar, 2026 First submitted to journal 12 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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